Extract insights in a 30TB time series workload with Amazon OpenSearch Serverless

This article discusses how to analyze 30TB time series datasets with Amazon OpenSearch Serverless. It highlights the innovations and optimizations that enable OpenSearch Serverless to support larger data sizes and provide faster responses.

Specifically, the article covers:

• Innovations like warm shard recovery prefetch, enhanced concurrency between coordinator and worker nodes, improved shard distribution, and dynamic sharding strategies to handle larger datasets and improve performance.
• A test methodology for ingesting and querying a 30TB dataset, including details on the data ingestion rate, auto-scaling behavior, and query performance metrics.
• Observations and results, including ingestion performance consistently over 2TB per day, and query performance metrics for different time ranges and query types.
• Conclusion encouraging readers to take advantage of the 30TB index support, improved throughput, and enhanced scaling capabilities of Amazon OpenSearch Serverless.